From Bits to Images : Inversion of Local Binary Descriptors

Local Binary Descriptors are becoming more and more popular for image matching tasks, especially when going mobile. While they are extensively studied in this context, their ability to carry enough information in order to infer the original image is seldom addressed. In this work, we leverage an inv...

Ausführliche Beschreibung

Bibliographische Detailangaben
Veröffentlicht in:IEEE transactions on pattern analysis and machine intelligence. - 1979. - 36(2014), 5 vom: 01. Mai, Seite 874-87
1. Verfasser: d'Angelo, Emmanuel (VerfasserIn)
Weitere Verfasser: Jacques, Laurent, Alahi, Alexandre, Vandergheynst, Pierre
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2014
Zugriff auf das übergeordnete Werk:IEEE transactions on pattern analysis and machine intelligence
Schlagworte:Journal Article Research Support, Non-U.S. Gov't
LEADER 01000caa a22002652 4500
001 NLM252590996
003 DE-627
005 20250219030418.0
007 cr uuu---uuuuu
008 231224s2014 xx |||||o 00| ||eng c
024 7 |a 10.1109/TPAMI.2013.228  |2 doi 
028 5 2 |a pubmed25n0841.xml 
035 |a (DE-627)NLM252590996 
035 |a (NLM)26353223 
040 |a DE-627  |b ger  |c DE-627  |e rakwb 
041 |a eng 
100 1 |a d'Angelo, Emmanuel  |e verfasserin  |4 aut 
245 1 0 |a From Bits to Images  |b Inversion of Local Binary Descriptors 
264 1 |c 2014 
336 |a Text  |b txt  |2 rdacontent 
337 |a ƒaComputermedien  |b c  |2 rdamedia 
338 |a ƒa Online-Ressource  |b cr  |2 rdacarrier 
500 |a Date Completed 25.11.2015 
500 |a Date Revised 10.09.2015 
500 |a published: Print 
500 |a Citation Status PubMed-not-MEDLINE 
520 |a Local Binary Descriptors are becoming more and more popular for image matching tasks, especially when going mobile. While they are extensively studied in this context, their ability to carry enough information in order to infer the original image is seldom addressed. In this work, we leverage an inverse problem approach to show that it is possible to directly reconstruct the image content from Local Binary Descriptors. This process relies on very broad assumptions besides the knowledge of the pattern of the descriptor at hand. This generalizes previous results that required either a prior learning database or non-binarized features. Furthermore, our reconstruction scheme reveals differences in the way different Local Binary Descriptors capture and encode image information. Hence, the potential applications of our work are multiple, ranging from privacy issues caused by eavesdropping image keypoints streamed by mobile devices to the design of better descriptors through the visualization and the analysis of their geometric content 
650 4 |a Journal Article 
650 4 |a Research Support, Non-U.S. Gov't 
700 1 |a Jacques, Laurent  |e verfasserin  |4 aut 
700 1 |a Alahi, Alexandre  |e verfasserin  |4 aut 
700 1 |a Vandergheynst, Pierre  |e verfasserin  |4 aut 
773 0 8 |i Enthalten in  |t IEEE transactions on pattern analysis and machine intelligence  |d 1979  |g 36(2014), 5 vom: 01. Mai, Seite 874-87  |w (DE-627)NLM098212257  |x 1939-3539  |7 nnns 
773 1 8 |g volume:36  |g year:2014  |g number:5  |g day:01  |g month:05  |g pages:874-87 
856 4 0 |u http://dx.doi.org/10.1109/TPAMI.2013.228  |3 Volltext 
912 |a GBV_USEFLAG_A 
912 |a SYSFLAG_A 
912 |a GBV_NLM 
912 |a GBV_ILN_350 
951 |a AR 
952 |d 36  |j 2014  |e 5  |b 01  |c 05  |h 874-87